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510(k) Data Aggregation
(120 days)
EASYCARE TX SYSTEM (CONNEXUNS)
EasyCare Tx is intended to be used with ResMed compatible therapy devices via the Tx Link. EasyCare Tx provides real-time data and treatment settings display, and can also provide therapy device setting changes remotely. EasyCare Tx is intended to be used in a clinical environment. The Tx Link is intended to provide connectivity between ResMed EasyCare Tx software and ResMed compatible therapy devices. The Tx Link relays real-time signals measured by the ResMed compatible therapy device to a polysomnograph (PSG). The Tx Link is intended to be used in a clinical environment.
ResMed's EasyCare Tx System enables clinicians to monitor real-time patient and flow generator information and adjust flow generator settings as required from the control room within the hospital and sleep lab clinical setting. The EasyCare Tx System includes: EasyCare Tx, a software application that executes on the end-user's PC and interfaces with the accessory Tx Link to view and set various flow generator parameters and settings; and Tx Link, a hardware accessory that connects to a flow generator and interfaces to a remote PC via an Ethernet connection. The Tx Link also provides analog flow generator signals to third party Polysomnograph (PSG) systems, such as Embla (K971813).
The provided text describes the EasyCare Tx System, a software application and hardware accessory designed to monitor and adjust settings of ResMed compatible therapy devices in a clinical environment. While the document mentions "predetermined acceptance criteria" and that all tests confirmed the product met these criteria, it does not explicitly detail the specific acceptance criteria or the study that quantitatively proves the device meets them.
The document states:
- "Design and Verification activities were performed on the EasyCare Tx System as a result of the risk analysis and design requirements. All tests confirmed the product met the predetermined acceptance criteria."
- "Performance testing of EasyCare Tx has been conducted using End-to-End bench testing methodology to demonstrate that the modified EasyCare Tx performs to design input specifications."
- "EasyCare Tx met the predetermined pass/fail criteria as defined in the EasyCare Tx System Verification Report!"
However, the "predetermined pass/fail criteria" or "predetermined acceptance criteria" are not listed or described in the provided text.
Based on the available information, here is a summary of what can and cannot be answered regarding acceptance criteria and the study that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria | Reported Device Performance |
---|---|
Not specified in the document | "All tests confirmed the product met the predetermined acceptance criteria." |
Not specified in the document | "EasyCare Tx met the predetermined pass/fail criteria as defined in the EasyCare Tx System Verification Report!" |
The document lacks specific, quantifiable acceptance criteria (e.g., accuracy percentages, latency thresholds, reliability metrics). It only states that the device successfully met these unspecified criteria.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document mentions "End-to-End bench testing methodology." This implies a simulated or lab-based environment rather than patient data. No sample size for a test set (e.g., number of patients, number of data points) is provided, nor is the data provenance (country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
No information is provided regarding experts, ground truth establishment, or their qualifications. Given the nature of the "End-to-End bench testing," it's likely that ground truth would be based on expected system outputs or specifications rather than expert interpretation of complex clinical data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
No information is provided regarding an adjudication method.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
The document explicitly states: "Clinical testing was not deemed necessary as indentified in the Risk Analysis, as EasyCare Tx only obtains patient and machine information from therapeutic devices; clinical trials have already been performed on the therapeutic devices and their algorithms. Accordingly, no clinical testing is required!"
Therefore, no MRMC comparative effectiveness study was done, and no effect size for human reader improvement with AI assistance can be reported from this document. The device is a system for monitoring and adjusting existing therapy devices, not an AI for interpretation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The performance testing was "End-to-End bench testing methodology." This would inherently be a standalone test of the software and hardware system against design specifications, without a human-in-the-loop component for the evaluation of its core functions (monitoring and adjusting settings).
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the "End-to-End bench testing" would be the design input specifications for the device's performance. The device is designed to accurately display real-time data and implement setting changes, implying that "ground truth" refers to the expected, correct display values and successful application of settings. It would not typically involve expert consensus, pathology, or outcomes data in the context of this device's function.
8. The sample size for the training set
No information regarding a training set is provided. The device is a system for data transfer and control, not a machine learning algorithm that typically requires a training set.
9. How the ground truth for the training set was established
Not applicable as there is no mention of a training set or machine learning.
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